An MCP server that provides standardized access to biomedical knowledge bases and resources, enabling AI systems to retrieve verified information from sources like bioRxiv, EuropePMC, and various protein/gene databases.
A MongoDB Atlas-based Notion-style knowledge base management MCP server that supports user workspaces, project management, page CRUD with tree structure, and text search.
A unified MCP server for biomedical research that connects AI systems to resources like Ensembl, EuropePMC, STRING, and more, enabling retrieval of verified domain-specific information.
A Model Context Protocol server that enables intelligent document search and retrieval from PDF collections, providing semantic search capabilities powered by OpenAI embeddings and ChromaDB vector storage.
Integrates Redshift database query capabilities with vector-based knowledgebase tools for semantic search and RAG applications. It enables users to execute SQL queries, explore database schemas, and perform hybrid semantic searches on markdown files stored in S3.
Provides redacted access to a private local knowledgebase for coding agents, allowing them to inspect files while hiding sensitive names and identifiers.
A standalone MCP server for exploring the weclapp REST API v2, providing offline knowledge about entities, endpoints, and relationships, plus optional live GET probes against a tenant.
Enables AI assistants to extract and analyze text content from various document formats (PDF, DOCX, PPTX, XLSX) in local knowledge bases, and create new formatted Word and Excel documents with structured data and reports.
An MCP server that enables AI assistants to access and search Cherry Studio knowledge bases, supporting operations like listing, searching, and retrieving details.
A minimal, production-ready FastMCP server template with auto-discovery, YAML configuration, authentication, and a knowledgebase, enabling quick scaffolding of new MCP servers.
An MCP-based AI agent that retrieves and processes documents to answer queries using a RAG pipeline with LangChain and Claude models. It enables document indexing, context-aware retrieval, and multi-tool orchestration for research and knowledgebase applications.
A high-precision local knowledge base server enabling AI agents to navigate, search, and reason about complex codebases using hybrid semantic, lexical, and graph retrieval.